WARNING THIS IS A EXPERIMENTAL object

We have not been able to test, simulate, or build datasets for this object. Use at your own risk. This analytic is NOT supported.

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Description

Detect Okta user lockout events

  • Type: Anomaly

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2020-07-21
  • Author: Rico Valdez, Splunk
  • ID: 62b70968-a0a5-4724-8ac4-67871e6f544d

Annotations

ATT&CK
ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Initial Access, Persistence, Privilege Escalation
T1078.001 Default Accounts Defense Evasion, Initial Access, Persistence, Privilege Escalation
Kill Chain Phase
  • Exploitation
NIST
  • DE.CM
CIS20
  • CIS 16
CVE 
1
2
3
4

`okta` displayMessage="Max sign in attempts exceeded" 
| rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city 
| table _time, user, country, state, city, src_ip 
| `okta_account_lockout_events_filter`

Macros

The SPL above uses the following Macros:

Note that okta_account_lockout_events_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required field

  • _time
  • displayMessage
  • client.geographicalContext.country
  • client.geographicalContext.state
  • client.geographicalContext.city

How To Implement

This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.

Known False Positives

None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor.

Associated Analytic story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

source | version: 2